Method and apparatus for computer-implemented traffic control of motor vehicles in a predetermined area

Abstract

Provided is a method and an apparatus for computer-implemented traffic control of motor vehicles in a predetermined area, in which, at predetermined intervals, respectively: values of traffic parameters are ascertained in the predetermined area by way of data capture, wherein at least some of the traffic parameters relate to the motor vehicles traveling in the predetermined area and the traffic parameters of a respective motor vehicle include its current position, direction of travel and speed; a set of optimized traffic control actions, which include the adjustment of variable traffic signaling devices, is determined by an optimization using a learned data-driven model and the optimized traffic control actions are carried out, wherein the optimization takes account of predicted air quality values and the data-driven model is learned by training data from a simulation.

1 . A method for computer-implemented traffic control of motor vehicles in a predetermined area, wherein, at predetermined intervals, respectively:
 values of traffic parameters are ascertained in the predetermined area by way of data capture, wherein at least some of the traffic parameters relate to the motor vehicles traveling in the predetermined area and the traffic parameters of a respective motor vehicle include its current position, direction of travel and speed;   a set of optimized traffic control actions, which comprise the adjustment of variable traffic signaling devices, is determined by an optimization using a learned data-driven model and the optimized traffic control actions are carried out;   wherein the learned data-driven model is configured to ascertain output quantities in the form of air quality values for a multiplicity of points in the predetermined area from input quantities in the form of values of the traffic parameters and wherein the data-driven model is learned from a simulation by training data sets, wherein a respective training data set have values of the traffic parameters and associated air quality values that are determined by way of the simulation;   wherein the optimization includes a prediction of air quality values, according to which values of the traffic parameters are respectively predicted proceeding from the ascertained values of the traffic parameters for different sets of traffic control actions, from which predicted values of the traffic parameters predicted air quality values for the multiplicity of points are ascertained by the learned data-driven model, and wherein the set of optimized traffic control actions is determined by the optimization from the different sets of traffic control actions on the basis of a number of optimization goals, which include at least one of the goal of the highest possible overall air quality taking account of all predicted air quality values for the multiplicity of points; and the goal of the highest possible partial air quality taking account of some of the predicted air quality values for some of the multiplicity of points.   
     
     
         2 . The method as claimed in  claim 1 , wherein the data-driven model is a neural network structure made of one or more neural networks. 
     
     
         3 . The method as claimed in  claim 1 , wherein the number of optimization goals further comprises the goal of the lowest possible variation of the predicted air quality values over the predetermined area. 
     
     
         4 . The method as claimed in  claim 1 , wherein the traffic parameters further contain at least one of the vehicle model of the respective motor vehicles and air quality measurements at a number of measurement points in the predetermined area. 
     
     
         5 . The method as claimed in  claim 1 , wherein the data capture comprises the capture of at least one of position, speed, direction of travel and the license plate of the respective motor vehicles using a multiplicity of cameras. 
     
     
         6 . The method as claimed in  claim 1 , wherein the data capture is configured in such a way that at least some of the traffic parameters are wirelessly transmitted by the motor vehicles and received by a multiplicity of receivers in the predetermined area. 
     
     
         7 . The method as claimed in  claim 1 , wherein the variable traffic signaling devices comprise at least one of traffic lights and road signs with a variable information content. 
     
     
         8 . The method as claimed in  claim 1 , wherein the optimized traffic control actions comprise actions that influence the local public transport system. 
     
     
         9 . The method as claimed in  claim 1 , wherein the optimized traffic control actions comprise diversion instructions, which are transmitted to at least some of the motor vehicles and which adapt the route of the navigation system in the corresponding motor vehicle. 
     
     
         10 . The method as claimed in  claim 1 , wherein the optimized traffic control actions cause one or more road sections in the predetermined area to be shut for at least some of the motor vehicles. 
     
     
         11 . The method as claimed in  claim 1 , wherein the simulation is continued on the basis of traffic parameters that are ascertained using the data capture during the method, as a result of which new training data sets are obtained, by which the learning of the data-driven model is continued during the method. 
     
     
         12 . An apparatus for computer-implemented traffic control of motor vehicles in a predetermined area, wherein the apparatus is configured to carry out a method in which, at predetermined intervals, respectively:
 values of traffic parameters are ascertained in the predetermined area by way of data capture, wherein at least some of the traffic parameters relate to the motor vehicles traveling in the predetermined area and the traffic parameters of a respective motor vehicle include its current position, direction of travel and speed;   a set of optimized traffic control actions, which have the adjustment of variable traffic signaling devices, is determined by an optimization using a learned data-driven model and the optimized traffic control actions are carried out;   wherein the learned data-driven model is configured to ascertain output quantities in the form of air quality values for a multiplicity of points in the predetermined area from input quantities in the form of values of the traffic parameters and wherein the data-driven model is learned from a simulation by training data sets, wherein a respective training data set includes values of the traffic parameters and associated air quality values that are determined by way of the simulation;   wherein the optimization includes a prediction of air quality values, according to which values of the traffic parameters are respectively predicted proceeding from the ascertained values of the traffic parameters for different sets of traffic control actions, from which predicted values of the traffic parameters predicted air quality values for the multiplicity of points are ascertained by the learned data-driven model, and wherein the set of optimized traffic control actions is determined by the optimization from the different sets of traffic control actions on the basis of a number of optimization goals, which include the goal of the highest possible overall air quality taking account of all predicted air quality values for the multiplicity of points and/or the goal of the highest possible partial air quality taking account of some of the predicted air quality values for some of the multiplicity of points.   
     
     
         13 . The apparatus as claimed in  claim 12 , wherein the apparatus is configured to carry out a method. 
     
     
         14 . A computer program product, comprising a computer readable hardware storage device having computer readable program code stored therein, said program code executable by a processor of a computer system to implement a method with program code stored on a machine-readable medium, for carrying out the method as claimed in  claim 1  when the program code is executed on a computer. 
     
     
         15 . A computer program with program code for carrying out the method as claimed in  claim 1  when the program code is executed on a computer. 
     
     
         16 . The method as claimed in  claim 8 , wherein the optimized traffic control actions comprise at least one of a change in the frequency of one or more lines of the local public transport system and a change in the capacity of transportation in the local public transport system. 
     
     
         17 . The method as claimed in  claim 10 , wherein the optimized traffic control actions cause one or more road sections in the predetermined area to be shut for motor vehicles with a certain type of engine.